{"id":37326,"date":"2019-10-09T10:47:54","date_gmt":"2019-10-09T17:47:54","guid":{"rendered":"https:\/\/newed.any0.dpdns.org\/industry\/blog\/?p=37326"},"modified":"2019-11-18T08:24:25","modified_gmt":"2019-11-18T16:24:25","slug":"how-tech-has-changed-three-key-roles-in-finance","status":"publish","type":"post","link":"https:\/\/newed.any0.dpdns.org\/en-us\/industry\/microsoft-in-business\/business-transformation\/2019\/10\/09\/how-tech-has-changed-three-key-roles-in-finance\/","title":{"rendered":"How tech has changed three key roles in finance"},"content":{"rendered":"

Dylan Dias | CEO, Neal Analytics<\/em><\/p>\n

These are exciting times to be in finance, as artificial intelligence, machine learning, automation<\/span>,<\/span>\u00a0and robotics\u00a0<\/span>are playing<\/span>\u00a0a rapidly increasing<\/span>\u00a0<\/span>role in the field. These technologies\u00a0<\/span>enable CFOs to work higher up the value chain<\/span><\/a>,\u00a0<\/span><\/i>a<\/span>nd savvy use of this te<\/span>ch<\/span> also frees up bandwidth across multiple functions within finance. Three roles<\/span>\u00a0\u2013 account<\/span>ant,<\/span>\u00a0analyst, and auditor \u2013<\/span>\u00a0have seen particularly dramatic shifts, allowing our most\u00a0<\/span>valuable asset<\/span>, our people, to do more of what they do best.<\/span>\u00a0<\/span><\/p>\n

Accounting team<\/span><\/b>\u00a0<\/span><\/p>\n

Accountants and bookkeepers have seen one of the most visible shifts, moving from piles of physical paperwork to fully digitized data, resulting in tremendous<\/span>\u00a0paperwork reduction<\/span><\/b>, from timesheets to contracts. Being able to move from manually inputting data to scanning and processing saves time and effort, which ultimately leads to\u00a0<\/span>cost\u00a0<\/span>savings.\u00a0<\/span>\u00a0<\/span><\/p>\n

In one case I was involved in, a team of four people was doing ad hoc manual data entry on invoices. Using\u00a0<\/span>Microsoft\u2019s optical character <\/span>recognition <\/span><\/a>technology, the key focus was extracting data fields from fax and email documents and having it automatically entered as an electronic record. The initial value-add from automation was about 25%. Over time, this creates a corpus that can be built up as confidence in the solution grows, improving error-handling as they go.<\/span>\u00a0<\/span><\/p>\n

Fuzzy matching<\/span><\/a>\u00a0is a form of artificial intelligence that compares two sets of\u00a0<\/span>data, and<\/span>\u00a0allows patterns from high-value documents to be applied to the lower-value documents. This automation enables handling further down the long tail, instead of letting lower-value pieces fall through the cracks. This allows the finance division to cover more ground with fewer people.\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n

An example is the handling of enterprise agreements and incentives with customers. Microsoft had a group of 50 CPAs manually going through these contracts, looking for specific, high-dollar performance guarantees. This solution applied fuzzy matching to surface smaller details from the long tail of the data set that would be prohibitively costly to do manually. It\u2019s a more thorough application of the business rule to the entire corpus,<\/span>\u00a0<\/span>reduc<\/span>ing<\/span>\u00a0risk. So<\/span>,<\/span>\u00a0it\u2019s a risk play, and it\u2019s a speed and agility play. You can cover more ground with fewer people.<\/span>\u00a0<\/span><\/p>\n

Finance Analyst\/ Manager<\/span><\/b>\u00a0<\/span><\/p>\n

The biggest change for the finance analyst or finance manager is in\u00a0<\/span>forecasting automation<\/span><\/b>. Better forecasts help companies plan and budget\u00a0<\/span>better, and<\/span>\u00a0save time in doing so. For a large enterprise with multiple lines of businesses, there will be hundreds of people involved in monthly and quarterly business reviews. Crunching these numbers is an opportunity for applying machine learning and analytics to increase the velocity of the forecasting rhythm.\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n

My colleague\u00a0<\/span>Jayson\u00a0<\/span>Stemmler<\/span><\/a>, a data scientist and project manager notes, \u201cWhere we see the biggest impact from a finance forecasting perspective is time savings.\u201d He explains, \u201cOne product rolling out now forecasts 700 or 800 different combinations of product segments and geography. To produce individual forecasts for each of those manually would take a large team a number of days\u00a0<\/span>\u2013\u00a0 we<\/span>\u00a0can do that now in about three hours.\u201d\u00a0<\/span>\u00a0<\/span><\/p>\n

When we apply<\/span>\u00a0<\/span>machine learning<\/span><\/a>\u00a0to forecasting<\/span>, we can<\/span>\u00a0help a company understand why it succeeds at its key driver for revenue. Whether the customer is a large beverage company or a nationwide tax preparer,\u00a0<\/span>to name two examples, we\u2019ve been able to\u00a0<\/span>apply machine learning to\u00a0<\/span>sales-driver analysis <\/span><\/b>and <\/span>found<\/span>\u00a0unexpected, actionable patterns\u00a0<\/span>influencing growth. We\u2019ve been able to<\/span>\u00a0reveal factors the company can control to increase their KPI, whether that\u2019s footfalls to tax offices or cases of soda sold.\u00a0<\/span>\u00a0<\/span><\/p>\n

Auditor<\/span><\/b>\u00a0<\/span><\/p>\n

In fraud prevention, we find that applying artificial intelligence speeds anomaly detection and strengthens\u00a0<\/span>early warning capability<\/span><\/b>. Another core benefit of AI is\u00a0<\/span>knowledge mining<\/span><\/b>. Dynamic pattern recognition enables organizations to crunch the numbers of a vast set of data to answer practical key questions. For a philanthropic organization those might include, \u201cWhere are the grants doing the most good? What programs have the best compliance?\u201d In work we do with\u00a0<\/span>one large philanthropy<\/span>, we are very aware that there is a vast spread in the personas using the data, from a desk worker in Seattle to a field officer in Kenya. Automation makes sure that each persona has access to the tools they need, in a form factor appropriate to the overall situation.<\/span>\u00a0<\/span><\/p>\n

A key piece of digital transformation<\/span><\/b>\u00a0<\/span><\/p>\n

As<\/span>\u00a0<\/span>digital transformation<\/span>\u00a0<\/span>enables these three key\u00a0<\/span>roles<\/span>\u00a0t<\/span>o generate\u00a0<\/span>more<\/span>\u00a0and more<\/span>\u00a0data<\/span>,<\/span>\u00a0maintain<\/span>ing<\/span>\u00a0<\/span>awareness of\u00a0<\/span>it all<\/span>\u00a0<\/span>can become an unexpected <\/span>challeng<\/span>e<\/span>.\u00a0<\/span>Ensuring<\/span>\u00a0<\/span>visibility across the<\/span>\u00a0entire<\/span>\u00a0<\/span>team\u00a0<\/span>a<\/span>nd\u00a0<\/span>keep<\/span>ing\u00a0<\/span>d<\/span>ata\u00a0<\/span>from\u00a0<\/span>falling between the cracks<\/span>\u00a0will allow everyone<\/span>\u00a0<\/span>in<\/span> the finance division and <\/span>the <\/span>organization<\/span>\u00a0as a whole<\/span>\u00a0to\u00a0<\/span>make better-informed decisions with<\/span>\u00a0higher<\/span>\u00a0confidence<\/span>, allowing companies to deliver on their core promises.<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Dylan Dias | CEO, Neal Analytics These are exciting times to be in finance, as artificial intelligence, machine learning, automation,\u00a0and robotics\u00a0are playing\u00a0a rapidly increasing\u00a0role in the field. These technologies\u00a0enable CFOs to work higher up the value chain,\u00a0and savvy use of this tech also frees up bandwidth across multiple functions within finance.<\/p>\n","protected":false},"author":182,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ep_exclude_from_search":false,"_classifai_error":"","_classifai_text_to_speech_error":"","footnotes":""},"categories":[1536],"post_tag":[],"content-type":[],"coauthors":[582],"class_list":["post-37326","post","type-post","status-publish","format-standard","hentry","category-business-transformation"],"yoast_head":"\nHow tech has changed three key roles in finance - Microsoft in Business Blogs<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/newed.any0.dpdns.org\/en-us\/industry\/microsoft-in-business\/business-transformation\/2019\/10\/09\/how-tech-has-changed-three-key-roles-in-finance\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How tech has changed three key roles in finance - Microsoft in Business Blogs\" \/>\n<meta property=\"og:description\" content=\"Dylan Dias | CEO, Neal Analytics These are exciting times to be in finance, as artificial intelligence, machine learning, automation,\u00a0and robotics\u00a0are playing\u00a0a rapidly increasing\u00a0role in the field. 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